1. Field of the Invention
The present invention relates to diagnostic x-ray imaging, and more particularly, to an x-ray imaging system that generates and displays a large compound image of a target object or structure by aligning smaller constituent images using semantic information extracted from the images.
2. Description of the Prior Art
In many diagnostic x-ray imaging situations, the target object to be imaged is much larger than the field of view of the imaging device. Even when it is possible to increase the field of view to cover the whole target object, the resulting image has insufficient resolution or possible geometric distortions in the off-center areas. It may also not be possible to cover the entire target object in one image because of the geometry or topology of the target object. It is nevertheless useful to present the entire target object in a single image to the human for the purpose of diagnosis. Moreover, it is important to compose the image with certain precision requirement for quantitative measurement in many clinical applications. For example, many musculoskeletal disorders such as scoliosis require the examination of the spine as a whole so that its geometry can be seen or measured. Due to the size of the spine, it is currently not possible to acquire a single x-ray image of the entire spine without adding significant distortions, deteriorating contrast or subjecting the patient to large x-ray doses. In present radiological practice, partial, overlapping constituent images are taken at several stations along the spine, starting from the back of the head down to the pelvis. The overlaps between the images can vary. The ability to view the entire object on a single image facilitates convenient and accurate diagnostic examination and measurement.
The traditional solution to this problem is to take a plurality of smaller x-ray images spanning the target object and manually assemble them into a larger whole. A human would line up two smaller images (films) by hand to identify the amount of overlap, cut one of the films to eliminate the overlap region on it and paste the two films together to form a larger image. Throughout this specification, the smaller images are referred to as images, to differentiate them from the larger, image. Adjacent constituent images are acquired with overlaps to facilitate later generation of the compound image.
There exist several prior art methods to mosaic constituent images into a larger whole, outside the realm of x-ray diagnostic imaging. Examples include U.S. Pat. No. 5,262,856 entitled "Video Image Compositing Techniques" issued on Nov. 16, 1993 and U.S. Pat. No. 5,649,032 entitled "System For Automatically Aligning Images To Form A Mosaic Image" issued on Jul. 15, 1997. Other examples are found in articles by P. Dani and S. Chaudhuri in "Automated Assembling Of Images: Image Montage Preparation", Pattern Recognition, vol. 28, no. 3, March 1995, pp. 431-445; by D. L. Milgram in "Computer Methods For Creating Photomosaics", Transactions on Computers, 1975, vol. 23, pp. 1113-1119 and by D. T. Pham, M. Abdollahi in "Automatic Assembly Of Ocular Fundus Images", Pattern Recognition, 1991, Vol. 24, No. 3, pp. 253-262. In x-ray diagnostic imaging, in addition to manual assembling of compound images, the prior art includes an automatic method to generate a compound image of the whole legs in peripheral angiography. This is described in U.S. Pat. No. 5,123,056 entitled "Whole-Leg X-Ray Image Processing And Display Techniques" issued on Jun. 16, 1992. U.S. Pat. No. 5,833,607 entitled "Automatic Full-leg Mosaic And Display For Peripheral Angiography", issued on Nov. 10, 1998 and assigned to the same assignees as the present invention also relates. U.S. Pat. No. 5,123,056 and U.S. Pat. No. 5,833,607 are hereby incorporated herein by reference.
When humans form compound diagnostic images manually, they make substantial use of visual knowledge of the target object or structures which are to be examined or measured in the compound image. However, few prior art automatic methods for image compositing extract or use semantic knowledge of the target object. Knowledge of semantically significant visual events in the constituent images, as well as knowledge about the purpose of compounding, can substantially improve the accuracy and efficiency of automatic image compositing. Explicit extraction and use of semantic knowledge for the purpose of diagnostic compound image generation is one object of the present invention.